What is the true efficacy of Pfizer’s vaccine. Bucci’s post

Peter Doshi's editorials on Pfizer vaccine, published on BMJ (of which he is editor), are making a lot of fury.

I have decided to address his arguments one at a time, but a premise is necessary first.

I fully agree with your call (followed by that of many others) to make clinical trial data completely transparent and complete.

On the other hand, this is a battle that has been going on for years, which certainly does not begin with the Sars-CoV-2 vaccine.

Freeing all clinical data: it is essential to have trust, security, tranquility.

Having said that, let's examine his arguments, starting with the first one, to whom this post is dedicated.

Based on the discovery that 3410 cases of "suspected Covid-19" are named in the FDA documents about the Pfizer vaccine trial, and on the basis that these are many more than the confirmed cases used to calculate the effectiveness of the vaccine, he argues You assert that the effectiveness could be much lower – even only 19% – because these thousands of cases of "suspected Covid-19" are distributed almost equally between vaccinated and unvaccinated. These thousands, of course, would weigh much, much more than the less than 200 confirmed cases, if they were indeed Covid-19 cases.

However, this is not the case, and indeed Peter Doshi writes in his January 4th editorial:

“If many or most of these suspected cases were in people who had a false negative PCR test result, this would dramatically decrease vaccine efficacy. But considering that influenza-like illnesses have always had myriad causes — rhinoviruses, influenza viruses, other coronaviruses, adenoviruses, respiratory syncytial virus, etc. — some or many of the suspected covid-19 cases may be due to a different causative agent ".

Why is Doshi forced to refer to “Covid-19 suspects” as people who have had a false negative PCR test?

Because the fact that the "Covid-19 suspects" are symptomatic and PCR negative people, is confirmed by the FDA documents where he found the news of the 3410 cases of " Covid-19 suspect".

The documents in fact report the following:

"Efficacy is being assessed throughout a participant's follow-up in the study through surveillance for potential cases of COVID-19. If, at any time, a participant develops acute respiratory illness, an illness visit occurs. Assessments for illness visits include a nasal (midturbinate) swab, which is tested at a central laboratory using a reverse transcription-polymerase chain reaction (RT-PCR) test (eg, Cepheid; FDA authorized under EUA), or other sufficiently validated nucleic acid amplification-based test (NAAT), to detect Sars-CoV-2. "

So if those 3410s were true Covid-19s and therefore Doshi's calculations were correct, we should also assume that they are all false PCR negatives; 3410 lost positives (i.e. false negatives) vs 200 (true) positives found, used to calculate vaccine efficacy by Pfizer; but this PCR error rate is completely unrealistic.

This being the case, the forecast of a substantial very low efficacy of the Pfizer vaccine (19% or 29% excluding "suspected Covid-19" found in the first week after the first dose), derived from considering the "suspected Covid-19" as false positive on PCR, it is certainly false.

As regards this first argument of Doshi, it seems clear to me, even from his own words, that he deliberately used an unrealistic borderline case and a paradoxical argument, to correctly draw attention to the fact that all the data must be provided anyway (even those on 3410 "suspected Covid-19"); which is by no means what so many believe they understand, assuming two hoaxes in one fell swoop – that the CRP is subject to a false negative rate of over 90% and that the Pfizer vaccine has been licensed with less than 50%.

I am ready to change my mind, should the data prove me wrong; but, for now, it seems to me that they point in a completely different direction compared to certain comments and blogs, even in prestigious magazines such as BMJ.